Nisansa Dilushan de Silva

I am a lecturer at the Department of Computer Science & Engineering, University of Moratuwa, Sri Lanka. I obtained my Ph.D (2020, advisor: Dejing Dou) and MS (2016) degrees in Computer and Information Science from University of Oregon, USA and my BSc (Hons) in Computer Science & Engineering (2011) degree from University of Moratuwa. I joined University of Moratuwa as a lecturer in 2011. From 2013 to 2014, I worked as a researcher at LIRNEasia. In 2018, I worked as a Givens Associate at Argonne National Laboratory, USA. I have over 80 peer reviewed publications in the field of computer science, mostly under the subfields of Natural Language Processing and Artificial Intelligence, earning more than 1400 citations. I am also an associate member of the IESL.

Professional Experience

  • Present 2020

    Senior Lecturer

    Department of Computer science & Engineering, University of Moratuwa,
    Sri Lanka

  • 2021 2020

    Research Fellow

    LIRNEasia,
    Sri Lanka

  • 2020 2014

    Graduate Research/Teaching Fellow

    University of Oregon, Department of Computer and Information Science,
    USA.

  • 2018 2018

    Givens Associate

    Argonne National Laboratory,
    USA.

  • 2020 2011

    Lecturer

    Department of Computer science & Engineering, University of Moratuwa,
    Sri Lanka

  • 2014 2013

    Researcher

    LIRNEasia,
    Sri Lanka

  • 2014 2013

    Visiting Lecturer

    Northshore College of Business and Technology,
    Sri Lanka

Education

  • Ph.D. 2020

    Ph.D. in Computer & Information Science

    University of Oregon, USA

  • MS 2016

    MS in Computer & Information Science

    University of Oregon, USA

  • BSc2011

    B.Sc Engineering (Hons)in Computer Science & Engineering

    University of Moratuwa, Sri Lanka

Featured Research

Discovering Inconsistencies in PubMed Abstracts Through Ontology-Based Information Extraction


N. de Silva, D. Dou, and J. Huang

Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, 2017, pp. 362--371,

Searching for a cure for cancer is one of the most vital pursuits in modern medicine. In that aspect microRNA research plays a key role. Keeping track of the shifts and changes in established knowledge in the microRNA domain is very important. In this paper, we introduce an Ontology-Based Information Extraction method to detect occurrences of inconsistencies in microRNA research paper abstracts. We propose a method to first use the Ontology for MIcroRNA Targets (OMIT) to extract triples from the abstracts. Then we introduce a new algorithm to calculate the oppositeness of these candidate relationships. Finally we present the discovered inconsistencies in an easy to read manner to be used by medical professionals. To our best knowledge, this study is the first ontology-based information extraction model introduced to find shifts in the established knowledge in the medical domain using research paper abstracts. We downloaded 36877 abstracts from the PubMed database. From those, we found 102 inconsistencies relevant to the microRNA domain.